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Day 1 • Tuesday, February 16 • Conference

7:00

Registration

9:00

Training: Advanced: Exploring Wikipedia with Spark

Training: Spark Essentials

Training: Data Science with Apache Spark

12:00

Lunch

1:00 PM

Training Continues: Spark Essentials

Training Continues: Data Science with Apache Spark

5:00 PM

End of Day 1

6:00 PM

Spark Meetup

Food. Drink. Spark! The tradition continues. We’ll have several speakers delving into Spark with us and hope to see you there. -Matt & Francois

 

Day 2 • Wednesday, February 17 • Conference

7:00

Registration

9:00

Spark 2.0

The next release of Spark will be 2.0, marking a big milestone for the project. In this talk, I’ll cover some of the large upcoming features that made us increase the version number to 2.0,… Read more
9:30

Democratizing Access to Data

Databricks’ vision is to make big data simple for the enterprise. In this keynote, Databricks co-founder and CEO – Ali Ghodsi – will announce the beta release of Databricks Community Edition, a free version of… Read more
9:50
10:00

Apache Spark: The Analytics Operating System

Apache Spark: The Analytics Operating System
10:10

Spark Usage in Core Enterprise Business Operations

In this keynote, SAP’s Ken Tsai will highlight how SAP HANA Vora extends Apache Spark to provide OLAP modeling capabilities and real-time query federation to enterprise data. You will learn real-world use cases where instant… Read more
10:20

Break — Sponsored by Databricks

11:00
Developer

Spark Performance: What's Next

Data Science

Distributed Time Travel for Feature Generation

11:35
Enterprise

Spark at Bloomberg

Data Science

Monte Carlo Simulations in Ad-Lift Measurement Using Spark

12:10
Enterprise

Spark and the Enterprise

Data Science

Using GraphX/Pregel on Browsing History to Discover Purchase Intent

12:45 PM

Lunch

1:50 PM
Developer

Magellan: Spark as a Geospatial Analytics Engine

Data Science

Building a Recommendation Engine Using Diverse Features

2:25 PM
3:00 PM
Developer

Building a Graph

Data Science

Time Series Analysis with Spark

3:30 PM

Break

4:00 PM
Enterprise

Spark and the Future of Advanced Analytics

Developer

Lambda at Weather Scale

Data Science

Generalized Linear Models in Spark MLlib and SparkR

4:35 PM
5:10 PM
Enterprise

5 Myths About Spark and Big Data (And Where It Goes Next)

Developer

Spark Tuning for Enterprise System Administrators

Data Science

Insights into Customer Behavior from Clickstream Data

6:00 PM

Attendee Reception in the Expo Hall

 

Day 3 • Thursday, February 18 • Conference

7:00

Registration

9:00
9:30

Leveraging Spark, AWS, and Graph Analytics to Better Protect Customers

In this keynote, Capital One’s Chris D’Agostino will highlight how Capital One is using Spark, Redshift and graph analytics to explore semantic relationships to better protect customers against credit card fraud. You will learn about… Read more
9:50

Data Profiling and Pipeline Processing with Spark

Come to this keynote to learn how Synchronoss, a predictive analytics provider for the telecommunications industry, leverages Spark to build a data profiling application which serves as a critical component in their overall framework for… Read more
10:10

Role of Spark in transforming eBay’s Enterprise Data Platform

eBay has one of the most mature Enterprise Data Platform’s in the industry with over 200PBs of data stored in our Hadoop and Teradata Warehouses. On average 30 TB of transactional and behavioral data is… Read more
10:30

Break

11:00
Applications

Spark Streaming and IoT

Research

Mapping Brain Connectivity Through Large-Scale Segmentation and Analysis

Developer

Structuring Spark: DataFrames, Datasets, and Streaming

11:35
Research

GraphFrames: Graph Queries in Spark SQL

Data Science

ggplot2.SparkR: Rebooting ggplot2 for Scalable Big Data Visualization

12:10
Applications

TopNotch: Systematically Quality Controlling Big Data

Developer

Beyond Collect and Parallelize for Tests

Data Science

Escaping Flatland: Interactive High-Dimensional Data Analysis in Drug Discovery Using Spark

12:45 PM

Lunch

1:50 PM
Applications

An Introduction to Sparkling Water

Research

Succinct Spark: Fast Interactive Queries on Compressed RDDs

Developer

Top 5 Mistakes When Writing Spark Applications

2:25 PM
Applications

Flintrock: A Faster, Better spark-ec2

Developer

Continuous Integration for Spark Apps

3:00 PM
Developer

Operational Tips for Deploying Spark

Data Science

Reactive Feature Generation with Spark and MLlib

3:30 PM

Break

4:00 PM
4:35 PM
Enterprise

Mastering Your Customer Data on Apache Spark

Developer

Enhancements on Spark SQL optimizer

5:10 PM
Developer

Pivoting Data with SparkSQL